• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.430-443
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• 2013

The recognition of current position and road surrounding of car is very important to driver for safe driving. This paper presents the recognition technique of the road traveling environment using position information hiding and viewpoint transform that monitors the information of road furniture and signature and notifies them to driver. The proposed scheme generates the road images into which the position information are hided, from car camera and GPS module and provides the road information to driver through the viewpoint transformation and the road signature detection. The driving tests with camera and GPS module verified that the position information hiding takes about 66.5ms per frame, the detection rate of road signature is about 95.83%, and the road signature detection takes about 227.45ms per frame. Therefore, we know that the proposed scheme can recognize the road traveling environment on the road video with 15 frame rate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.4
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• pp.393-400
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• 2014

In this study, an automatic transmission was developed for a bicycle. This transmission uses the pedal rpm and riding speed information for efficient riding. This transmission was installed on a bicycle using an internally geared hub. The automatic transmission was developed for a beginner to ride with proper gear changes. Indoor ride tests were performed to assess the performance of this transmission. Here, a 'beginner' is defined as a bicycle rider who can maintain a riding power of ~150W with a maximum heart rate of ~80%. Furthermore, 'ride with proper gear change' means that the rider could ride the bicycle while maintaining an efficient pedal rpm by the automatic transmission. One expert and four beginners participated in the ride test. The expert was chosen for the comparison with the beginners. To minimize environmental disturbances, the ride test was performed indoors. In this test, two types of gear changes manual and automatic were tested on two types of roads a road with a gradual incline of 0-3% and a road that simulates the bicycle road along the Han river in Seoul. The results of the ride tests show that the algorithm applied for the automatic transmission helps beginners to ride the bicycle efficiently.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.369-374
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• 2014

Path generation methods are required for safe and efficient driving in unmanned autonomous vehicles. There are two kinds of paths: global and local. A global path consists of all the way points including the source and the destination. A local path is the trajectory that a vehicle needs to follow from a way point to the next in the global path. In this paper, we propose a novel method for local path generation through machine learning, with an effective curve function used for initializing the trajectory. First, reinforcement learning is applied to a set of candidate paths to produce the best trajectory with maximal reward. Then the optimal steering angle with respect to the trajectory is determined by training an artificial neural network. Our method outperformed existing approaches and successfully found quality paths in various experimental settings, including the cases with obstacles.

• Journal of Navigation and Port Research
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• v.38 no.5
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• pp.493-501
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• 2014

An automated lifting vehicle(ALV) used in an automated container terminal is a type of unmanned vehicle that can self-lift a container as well as self-transport it to a destination. To operate a fleet of ALVs efficiently, one needs to be able to determine a minimum-time route to a given destination whenever an ALV is to start its transport job. To find a route free from any collision or deadlock, the occupation time of the ALV on each segment of the route should be carefully scheduled to avoid any such hazard. However, it is not easy because not only the travel times of ALVs are uncertain due to traffic condition but also the operation times of cranes en route are not predicted precisely. In this paper, we propose a routing method based on an ant colony optimization algorithm that takes into account these uncertainties. The result of simulation experiment shows that the proposed method can effectively find good routes under uncertainty.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.153-161
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• 2015

In the present study, as part of the technology development (Quality of Life Technology, QoLT) to improve the socio-economic status of people with disabilities as an extension of these studies, we propose the development of the smart wheelchair system and navigation technology for stable and safe driving in various environments. For the disabled and the elderly make driving easy and convenient with manual/autonomous driving condition, we firstly develop the user-oriented smart wheelchair system with optimized sensors for environment recognition, and then we propose a navigation framework of a hierarchical structure to ensure real-time response, as well as driving stability when traveling to various environmental changes, and to enable a more efficient operation. From the result of several independent experiments, we ensure efficiency and safety of smart wheelchair and its navigation system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.146-159
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• 2021

vehicle simulator as part of an empirical analysis the driving characteristics of elderly drivers. To this end, the driving characteristics of the elderly driver from previous study review. he driving characteristics of the elderly the driving elderly driver and general driverIn summarizing these experimental results, the -test showed different driving characteristics from general drivers in all items except for one side of the lane, such as driving speed and driving operation (brake, throttle, steering operation) at a significance level of 95%. Second, when changing lanes, it was difficult for elderly driver to maintain speed and secure an appropriate distance between carslderly driver changed lanes even in inappropriate situations (short distances between cars). Third, in unexpected situation, elderly drivers needed more distance and time.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.56-60
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• 1999

본 논문은, 자동차에서 발생할 수 있는 다양한 형태의 잡음이 섞인 음성을 대상으로, 잡음에 강인한 파라미터들을 사용하여 인식기들을 구축하였으며, 이들 파라미터를 비교 평가하였다. 실험에 사용된 음성 데이터는 차종, 속도, 도로 환경, 라디오 ON/OFF, 창문 개폐여부 등 다양한 잡음 환경에서 수집하였다. 실험에서 비교된 파라미터는 MFCC(Mel-Blrequency Cepstral Coefficient)와 PLP(Perceptually Linear Prediction) 이며, 각각의 파라미터에 대해서 MKM(Modified k-mean)을 이용하여 코드북을 작성하였고, DHMM(Discrete Hidden Markov Model)을 인식알고리즘으로 사용하였다. 실험 결과로서, 아스팔트 도로에서 창문을 닫고, 라디오를 켜지 않은 상태에서 60km/h로 주행시 $96.25\%$로 가장 높은 인식률을 얻었고, 고속도로에서 창문을 열고 100km/h로 주행시에는$60\%$로 가장 낮은 인식률을 얻었다.

• Proceedings of the KIEE Conference
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• 2005.07c
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• pp.2351-2353
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• 2005

본 논문은 포장도로의 표면 상태를 고성능의 레이저 변위 센서를 사용하여 정밀하게 측정하고, GPS(Global Positioning System)를 사용하여 측정 위치 데이터를 획득하는 도로 표면 측정 장비 개발에 관한 논문이다. 본 연구에서는 전체 시스템을 설계하고, 차량 주행을 모사한 실험 모형을 제작하여 실내 실험을 실시하였으며, GPS 단말기로부터 실시간으로 위치 신호를 수신하여 도로면 데이터와 연동할 수 있도록 하였다. 그리고 평가 차량의 전면에 레일(rail)을 장착하여 레이저 변위 센서가 좌우로 왕복운동이 가능하도록 하였으며, 레일을 작동시킨 상태에서 도로면을 측정해 보았다. 실험 모형의 측정 곁과는 차량이 80km/h로 주행할 때 도로 표지 타이닝(tinning)의 폭 오차 3.24%, 깊이 오차 5%였다. 차량이 정지된 상태에서 레일을 작동시켜 요철을 측정하였을 경우 레일 방향에 대한 폭 오차는 0.07%였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.246-263
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• 2023

The stabilization time of take-over refers to the time it takes for driving to stabilize after the take-over. Following a take-over request from an automated driving system, the driver must become aware of the road driving environment and perform manual driving, making it crucial to clearly understand the relationship between the driving environment and stabilization time of take-over. However, previous studies specifically focusing on stabilization time after take-over are rare, and research considering the driving environment is also lacking. To address this, our study conducted experiments using a driving simulator to observe take-over transitions. The results were analyzed using a liner mixed model to quantitatively identify the driving environment factors affecting the stabilization time of take-over. Additionally, coefficients for stabilization time based on each influencing factor were derived.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1034-1041
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• 2014

This paper propose a fuzzy inference model for obstacle avoidance for a mobile robot with an active camera, which is intelligently searching the goal location in unknown environments using command fusion, based on situational command using an vision sensor. Instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. In this paper, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. We describe experimental results obtained with the proposed method that demonstrate successful navigation using real vision data.